Copertina

Semantic Communication-Enhanced Split Federated Learning for Vehicular Networks: Architecture, Challenges, and Case Study

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yu, Lu, Chang, Zheng, Liang, Ying-Chang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks
di: Yu, Lu, et al.
Pubblicazione: (2024)

AIGC-assisted Federated Learning for Edge Intelligence: Architecture Design, Research Challenges and Future Directions
di: Qiang, Xianke, et al.
Pubblicazione: (2025)

Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing
di: Qiang, Xianke, et al.
Pubblicazione: (2024)

Deploying Large AI Models on Resource-Limited Devices with Split Federated Learning
di: Qiang, Xianke, et al.
Pubblicazione: (2025)

TSFLora: Token-Compressed Split Fine-Tuning for Wireless Edge Networks
di: Qiang, Xianke, et al.
Pubblicazione: (2026)

Age-Based Device Selection and Transmit Power Optimization in Over-the-Air Federated Learning
di: Liu, Jingyuan, et al.
Pubblicazione: (2025)

Semantic-Aware Cooperative Communication and Computation Framework in Vehicular Networks
di: Zhang, Jingbo, et al.
Pubblicazione: (2025)

Federated Learning for Tabular Data using TabNet: A Vehicular Use-Case
di: Lindskog, William, et al.
Pubblicazione: (2024)

Mobility-Aware Federated Self-supervised Learning in Vehicular Network
di: Gu, Xueying, et al.
Pubblicazione: (2024)

An Operator Splitting View of Federated Learning
di: Malekmohammadi, Saber, et al.
Pubblicazione: (2021)

Separate Aggregation of Split Network for Personalized Federated Learning
di: Kang, Yunseok, et al.
Pubblicazione: (2026)

Efficient Split Federated Learning for Large Language Models over Communication Networks
di: Zhao, Kai, et al.
Pubblicazione: (2025)

Deep Neural Network-Driven Adaptive Filtering
di: Wang, Qizhen, et al.
Pubblicazione: (2025)

Towards Secure and Efficient Data Scheduling for Vehicular Social Networks
di: Xia, Youhua, et al.
Pubblicazione: (2024)

Mobility-Aware Federated Learning: Multi-Armed Bandit Based Selection in Vehicular Network
di: Tu, Haoyu, et al.
Pubblicazione: (2024)

FedsLLM: Federated Split Learning for Large Language Models over Communication Networks
di: Zhao, Kai, et al.
Pubblicazione: (2024)

SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning
di: Shan, Yimeng, et al.
Pubblicazione: (2026)

Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
di: Papageorgiou, Yiannis, et al.
Pubblicazione: (2026)

Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks
di: Chen, Tan, et al.
Pubblicazione: (2024)

Federated Contrastive Learning for Personalized Semantic Communication
di: Wang, Yining, et al.
Pubblicazione: (2024)

Federated Learning with Enhanced Privacy via Model Splitting and Random Client Participation
di: Li, Yiwei, et al.
Pubblicazione: (2025)

An Efficient Federated Learning Framework for Training Semantic Communication System
di: Nguyen, Loc X., et al.
Pubblicazione: (2023)

Communication and Computation Efficient Split Federated Learning in O-RAN
di: Gu, Shunxian, et al.
Pubblicazione: (2025)

Ampere: Communication-Efficient and High-Accuracy Split Federated Learning
di: Zhang, Zihan, et al.
Pubblicazione: (2025)

SplitFedZip: Learned Compression for Data Transfer Reduction in Split-Federated Learning
di: Shiranthika, Chamani, et al.
Pubblicazione: (2024)

ELSA: Efficient LLM-Centric Split Aggregation for Privacy-Aware Hierarchical Federated Learning over the Network Edge
di: Yang, Xiaohong, et al.
Pubblicazione: (2026)

Secure Cluster-Based Hierarchical Federated Learning in Vehicular Networks
di: HaghighiFard, M. Saeid, et al.
Pubblicazione: (2025)

mixEEG: Enhancing EEG Federated Learning for Cross-subject EEG Classification with Tailored mixup
di: Liu, Xuan-Hao, et al.
Pubblicazione: (2025)

FedLion: Faster Adaptive Federated Optimization with Fewer Communication
di: Tang, Zhiwei, et al.
Pubblicazione: (2024)

FSSC: Federated Learning of Transformer Neural Networks for Semantic Image Communication
di: Yan, Yuna, et al.
Pubblicazione: (2024)

VoI-Driven Joint Optimization of Control and Communication in Vehicular Digital Twin Network
di: Lei, Lei, et al.
Pubblicazione: (2025)

Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection
di: HaghighiFard, M. Saeid, et al.
Pubblicazione: (2024)

Targeted Attacks and Defenses for Distributed Federated Learning in Vehicular Networks
di: Demir, Utku, et al.
Pubblicazione: (2025)

Non-Federated Multi-Task Split Learning for Heterogeneous Sources
di: Zheng, Yilin, et al.
Pubblicazione: (2024)

RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations
di: Xue, Chang, et al.
Pubblicazione: (2025)

Federated Split Learning with Improved Communication and Storage Efficiency
di: Mu, Yujia, et al.
Pubblicazione: (2025)

Improving Pattern Recognition of Scheduling Anomalies through Structure-Aware and Semantically-Enhanced Graphs
di: Lyu, Ning, et al.
Pubblicazione: (2025)

Anti-Byzantine Attacks Enabled Vehicle Selection for Asynchronous Federated Learning in Vehicular Edge Computing
di: Zhang, Cui, et al.
Pubblicazione: (2024)

Split Knowledge Distillation for Large Models in IoT: Architecture, Challenges, and Solutions
di: Li, Zuguang, et al.
Pubblicazione: (2024)

Personalized Hierarchical Split Federated Learning in Wireless Networks
di: Pervej, Md-Ferdous, et al.
Pubblicazione: (2024)